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STATISTICAL INFERENCE VIA BOOTSTRAPPING FOR MEASURES OF INEQUALITY

✍ Scribed by JEFFREY A. MILLS; SOURUSHE ZANDVAKILI

Publisher
John Wiley and Sons
Year
1997
Tongue
English
Weight
174 KB
Volume
12
Category
Article
ISSN
0883-7252

No coin nor oath required. For personal study only.

✦ Synopsis

In this paper we consider the use of bootstrap methods to compute interval estimates and perform hypothesis tests for decomposable measures of economic inequality. Two applications of this approach, using the Gini coecient and Theil's entropy measures of inequality, are provided. Our ®rst application employs preand post-tax aggregate state income data, constructed from the Panel Study of Income Dynamics. We ®nd that although casual observation of the inequality measures suggests that the post-tax distribution of income is less equal among states than pre-tax income, none of these observed dierences are statistically signi®cant at the 10% level. Our second application uses the National Longitudinal Survey of Youth data to study youth inequality. We ®nd that youth inequality decreases as the cohort ages, but between age-group inequality has increased in the latter half of the 1980s. The results suggest that (1) statistical inference is essential even when large samples are available, and (2) the bootstrap procedure appears to perform well in this setting.

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